A Survey Of Methods For Explaining Black Box Models

6 February 2018

Papers citing "A Survey Of Methods For Explaining Black Box Models"

50 / 410 papers shown

Title
InfFeed: Influence Functions as a Feedback to Improve the Performance of Subjective Tasks Somnath Banerjee Maulindu Sarkar Punyajoy Saha Binny Mathew Animesh Mukherjee TDI 34 0 0 22 Feb 2024
On Explaining Unfairness: An Overview Christos Fragkathoulas Vasiliki Papanikou Danae Pla Karidi E. Pitoura XAI FaML 19 2 0 16 Feb 2024
Explaining Probabilistic Models with Distributional Values Luca Franceschi Michele Donini Cédric Archambeau Matthias Seeger FAtt 37 2 0 15 Feb 2024
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 25 5 0 09 Feb 2024
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research Sicong Cao Xiaobing Sun Ratnadira Widyasari David Lo Xiaoxue Wu ... Jiale Zhang Bin Li Wei Liu Di Wu Yixin Chen 33 6 0 26 Jan 2024
Explainable Bayesian Optimization Tanmay Chakraborty Christin Seifert Christian Wirth 61 5 0 24 Jan 2024
Deep spatial context: when attention-based models meet spatial regression Paulina Tomaszewska El.zbieta Sienkiewicz Mai P. Hoang Przemysław Biecek 21 1 0 18 Jan 2024
Robust Stochastic Graph Generator for Counterfactual Explanations Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo CML 13 3 0 18 Dec 2023
Perceptual Musical Features for Interpretable Audio Tagging Vassilis Lyberatos Spyridon Kantarelis Edmund Dervakos Giorgos Stamou 32 5 0 18 Dec 2023
Accelerating the Global Aggregation of Local Explanations Alon Mor Yonatan Belinkov B. Kimelfeld FAtt 29 3 0 13 Dec 2023
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust Roel W. Visser Tobias M. Peters Ingrid Scharlau Barbara Hammer 23 5 0 04 Dec 2023
Machine Learning For An Explainable Cost Prediction of Medical Insurance U. Orji Elochukwu A. Ukwandu 26 31 0 23 Nov 2023
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 29 0 0 20 Nov 2023
Deep Natural Language Feature Learning for Interpretable Prediction Felipe Urrutia Cristian Buc Valentin Barriere 26 1 0 09 Nov 2023
Notion of Explainable Artificial Intelligence -- An Empirical Investigation from A Users Perspective A. Haque A. Najmul Islam Patrick Mikalef 36 1 0 01 Nov 2023
Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning E. Panagiotou Eirini Ntoutsi CML OffRL BDL 25 0 0 01 Nov 2023
A Mass-Conserving-Perceptron for Machine Learning-Based Modeling of Geoscientific Systems Yuan-Heng Wang Hoshin V. Gupta AI4CE 35 6 0 12 Oct 2023
Explaining Deep Face Algorithms through Visualization: A Survey Thrupthi Ann S. M. I. C. V. Balasubramanian M. Jawahar CVBM 34 1 0 26 Sep 2023
An AI Chatbot for Explaining Deep Reinforcement Learning Decisions of Service-oriented Systems Andreas Metzger Jon Bartel Jan Laufer 24 2 0 25 Sep 2023
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis Anahid N. Jalali Bernhard Haslhofer Simone Kriglstein Andreas Rauber FAtt 37 4 0 21 Sep 2023
Beyond XAI:Obstacles Towards Responsible AI Yulu Pi 37 2 0 07 Sep 2023
Ensemble of Counterfactual Explainers Riccardo Guidotti Salvatore Ruggieri CML 16 8 0 29 Aug 2023
SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator Lev V. Utkin Danila Eremenko A. Konstantinov 32 4 0 07 Aug 2023
Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model Khushnaseeb Roshan Aasim Zafar 17 16 0 31 Jul 2023
Toward Transparent Sequence Models with Model-Based Tree Markov Model Chan Hsu Wei Huang Jun-Ting Wu Chih-Yuan Li Yihuang Kang 31 0 0 28 Jul 2023
Assessment of the suitability of degradation models for the planning of CCTV inspections of sewer pipes Fidae El Morer Stefan H. A. Wittek Andreas Rausch 19 3 0 12 Jul 2023
A User Study on Explainable Online Reinforcement Learning for Adaptive Systems Andreas Metzger Jan Laufer Felix Feit Klaus Pohl OffRL OnRL 24 1 0 09 Jul 2023
Reliable AI: Does the Next Generation Require Quantum Computing? Aras Bacho Holger Boche Gitta Kutyniok 26 2 0 03 Jul 2023
Towards Explainable TOPSIS: Visual Insights into the Effects of Weights and Aggregations on Rankings R. Susmaga Izabela Szczech D. Brzezinski 20 16 0 13 Jun 2023
Explainable Predictive Maintenance Sepideh Pashami Sławomir Nowaczyk Yuantao Fan Jakub Jakubowski Nuno Paiva ... Bruno Veloso M. Sayed-Mouchaweh L. Rajaoarisoa Grzegorz J. Nalepa João Gama 32 8 0 08 Jun 2023
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits Zhuokai Zhao Takumi Matsuzawa W. Irvine Michael Maire G. Kindlmann 45 2 0 31 May 2023
Reason to explain: Interactive contrastive explanations (REASONX) Laura State Salvatore Ruggieri Franco Turini LRM 30 1 0 29 May 2023
The Case Against Explainability Hofit Wasserman Rozen N. Elkin-Koren Ran Gilad-Bachrach AILaw ELM 31 1 0 20 May 2023
BELLA: Black box model Explanations by Local Linear Approximations N. Radulovic Albert Bifet Fabian M. Suchanek FAtt 37 1 0 18 May 2023
Open problems in causal structure learning: A case study of COVID-19 in the UK Anthony C. Constantinou N. K. Kitson Yang Liu Kiattikun Chobtham Arian Hashemzadeh Praharsh Nanavati R. Mbuvha Bruno Petrungaro CML 32 9 0 05 May 2023
The Power of Typed Affine Decision Structures: A Case Study Gerrit Nolte Maximilian Schlüter Alnis Murtovi Bernhard Steffen AAML 20 3 0 28 Apr 2023
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring Nijat Mehdiyev Maxim Majlatow Peter Fettke 30 2 0 12 Apr 2023
Learning Optimal Fair Scoring Systems for Multi-Class Classification Julien Rouzot Julien Ferry Marie-José Huguet FaML 19 8 0 11 Apr 2023
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When? M. Rubaiyat Hossain Mondal Prajoy Podder 26 56 0 10 Apr 2023
Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models Emilio Ferrara SILM 36 247 0 07 Apr 2023
Local Interpretability of Random Forests for Multi-Target Regression Avraam Bardos Nikolaos Mylonas Ioannis Mollas Grigorios Tsoumakas AAML 19 2 0 29 Mar 2023
Improving Prediction Performance and Model Interpretability through Attention Mechanisms from Basic and Applied Research Perspectives Shunsuke Kitada FaML HAI AI4CE 32 0 0 24 Mar 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals Greta Warren Markt. Keane Christophe Guéret Eoin Delaney 26 13 0 16 Mar 2023
"How to make them stay?" -- Diverse Counterfactual Explanations of Employee Attrition André Artelt Andreas Gregoriades 31 5 0 08 Mar 2023
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning Jasmina Gajcin Ivana Dusparic CML 32 3 0 08 Mar 2023
Learning Human-Compatible Representations for Case-Based Decision Support Han Liu Yizhou Tian Chacha Chen Shi Feng Yuxin Chen Chenhao Tan 28 5 0 06 Mar 2023
NxPlain: Web-based Tool for Discovery of Latent Concepts Fahim Dalvi Nadir Durrani Hassan Sajjad Tamim Jaban Musab Husaini Ummar Abbas 15 1 0 06 Mar 2023
A System's Approach Taxonomy for User-Centred XAI: A Survey Ehsan Emamirad Pouya Ghiasnezhad Omran A. Haller S. Gregor 31 1 0 06 Mar 2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 35 2 0 01 Mar 2023
Concept Learning for Interpretable Multi-Agent Reinforcement Learning Renos Zabounidis Joseph Campbell Simon Stepputtis Dana Hughes Katia P. Sycara 39 15 0 23 Feb 2023